基于模糊神经网络参数整定的仿人智能控制  

Human-simulated intelligent control based on parameters correcting by fuzzy neural network

作　　者：张贯宇[1] 田建艳[1,2] 张维杰[1] 邱华东[3] 张婵爱[1] 

机构地区：[1]太原理工大学,山西太原030024 [2]新型传感器与智能控制教育部重点实验室,山西太原030024 [3]太原钢铁集团有限公司热连轧厂,山西太原030003

出　　处：《传感器与微系统》2013年第10期30-33,共4页Transducer and Microsystem Technologies

基　　金：山西省自然科学基金资助项目(2010011022-3)

摘　　要：针对目前带钢厚度控制精度低,不能满足生产要求的问题,将模糊神经网络与仿人智能控制有机结合,设计了一种基于模糊神经网络参数整定的热轧带钢厚度仿人智能控制策略,利用模糊神经网络对仿人智能控制器的参数进行了整定。Matlab仿真结果表明:基于模糊神经网络参数整定的仿人智能控制优于PID控制,为解决复杂工业过程的控制提供了一种新的、有效的方法。Aiming at problem of low control precision and cannot meet requirement of production of strip thickness,combines fuzzy neural network with human-simulated intelligent control technology, design humansimulated intelligent control strategy of hot roiled strip steel thickness based on fuzzy neural network parameters setting, correct human-simulated intelligent controller parameters using fuzzy neural network. The simulation experiment result by Matlab shows that the human-simulated intelligent control method which based on fuzzy neural network has a better performance compared with PID control,it can provide a new effective method for the control of complex industrial process.

关 键 词：仿人智能控制 模糊神经网络 参数整定 热轧带钢厚度控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]